The Huangshui National Wetland Park (HNWP) is a unique national wetland park in a city on the Qinghai-Tibetan Plateau, containing three zones: Haihu, Beichuan, and Ninghu. In this study, a total of 54 soil samples (18 sampling points with depths of 0–10 cm, 10–20 cm, and 20–30 cm) were collected in these three zones, and the contents of heavy metals (Cr, Cd, Cu, Hg, Ni, Pb, Zn, and As) of each sample were determined. The ecological risk of eight kinds of heavy metals was evaluated by using the geo–accumulation index ($I_{geo}$), and the ecological risk–controlling effect of the Xining urban wetlands on heavy metals was explored by comparative analysis, and the possible sources of heavy metals in the soil were analyzed via correlation analysis and principal component analysis (PCA). The results revealed that the total heavy metal concentration order was Haihu > Beichuan > Ninghu zone. As and Cu presented vertical accumulation characteristics in the surface and lower horizon, respectively. Cr, Cd, Hg, Ni, Pb, and Zn accumulated downwards along the depth. On the spatial scale, the enrichments of Cd and Hg brought non-negligible ecological risks in plateau urban wetlands. The results of PCA indicated that soil heavy metals mainly came from compound sources of domestic and atmospheric influences, traffic pollution sources, and industrial pollution sources. The study has revealed that human activities have inevitable negative impacts on wetland ecosystems, while the HNWP provides a significant weakening effect on heavy metal pollution.

The water level of Qinghai Lake, the largest saltwater lake in China, has been rising consistently, which has altered the lake’s ecosystem service patterns and produced an unpredictable impact on local ecological security and sustainable development. To explore the changes in the area around Qinghai Lake’s ecosystem provisioning services that respond to the rise in water level, the spatial and temporal changes of three ecosystem services (water yield, soil conservation, and habitat quality) from 2000 to 2020 were calculated by the InVEST model. Then, the ecosystem service transformation of the rise in Qinghai Lake’s underwater level was evaluated, and the trade-off and synchrony among the three ecosystem services were discussed. Finally, Random Forest and Geographically and Temporally Weighted Regression models were used, to reveal the driving factors and spatial differentiation of ecosystem service change. Results showed that: (1) Although three ecosystem provisioning services were increased by 3.21%, 31.67%, and 6.19%, respectively, in 2000–2020, an overall change trend was observed that they increased first and then decreased. After reaching their peak values in 2005 (444.68 mm), 2015 (341.89 t·hm⁻²·a⁻¹) and 2015 (0.67), three ecosystem provisioning services decreased to 349.27 mm, 271.82 t·hm⁻²·a⁻¹, and 0.66 in 2020, respectively. (2) Three ecosystem provisioning services, as well as ecosystem services among different land use types, presented a synchronous relationship during the research periods. (3) Natural factors, such as precipitation and NDVI (Normalized Difference Vegetation Index), accounted for 30.0% of ecosystem services changes, and Social-economic factors, such as GDP (Gross Domestic Product) and population accounted for 28.0% of three ecosystem provisioning services changes. These driving factors exhibited significant spatial heterogeneity (adjusted R² > 0.6). There were limitations in the scope of ecosystem services evaluation and insufficient consideration of the value of aquatic habitats, which deserved further exploration. This study may provide a scientific basis for the evaluation and management of the plateau lake ecosystem under the background of climate change.

The alpine marsh wetlands in the Qilian Mountains of Qinghai (QMQ) are under constant threat from the effects of climate change and human activities. Identifying the key ecological protection areas (KEPAs) of marsh wetlands is the prerequisite for formulating protection strategies and executing spatial planning programs. The current study developed a novel method to identify the KEPAs of marsh wetlands by following the ecosystem pattern–characteristics–functions (EPCFs) combined method and the ecological source–ecological corridor–ecological node research paradigm. More specifically, an evaluation system for ecological resistance was constructed by integrating the drivers of EPCFs in the marsh wetlands. Additionally, the marsh wetland degradation disturbances were analyzed through the drivers of EPCFs incorporated with a field survey. The findings indicated the following: (1) The marsh wetlands had a total water yield of approximately 3.96 × 10⁸ m³. The soil conservation rate and habitat quality per unit area were calculated to be 52.92 t·hm⁻²·a⁻¹ and 0.992, respectively, with higher values observed on the southern bank and lower values on the northern bank of the river in the QMQ. (2) The KEPAs for the marsh wetlands covered a total extent of 996.53 km² in the QMQ, encompassing 40 ecological sources, 39 ecological corridors, and 40 ecological nodes, predominantly located in the river source regions. (3) The KEPAs were restructured into an ecological framework comprising two ecological axes, four ecological belts, four ecological cores, and multiple nodes in the QMQ. In response to the factors contributing to the degradation of marsh wetlands, adaptive measures including prioritizing natural restoration, modifying grazing strategies, executing ecological restoration projects as a minimum, and designating protected areas have been recommended. This research could contribute to enhancing the efficiency of regional territorial planning and offer a theoretical foundation for improving the ecological protection framework of regional marsh wetlands.